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cbrt_op.cc
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cbrt_op.cc
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#include "caffe2/operators/cbrt_op.h"
#include "caffe2/utils/eigen_utils.h"
#include <algorithm>
#include <functional>
#include <string>
namespace caffe2 {
template <>
template <typename T>
bool CbrtGradientFunctor<CPUContext>::Forward(
const std::vector<int>& dY_dims,
const std::vector<int>& /* Y_dims */,
const T* dY,
const T* Y,
T* dX,
CPUContext* /* context */) const {
const int size = std::accumulate(
// NOLINTNEXTLINE(modernize-use-transparent-functors)
dY_dims.cbegin(), dY_dims.cend(), 1, std::multiplies<int>());
EigenVectorMap<T>(dX, size) = ConstEigenVectorArrayMap<T>(dY, size) /
ConstEigenVectorArrayMap<T>(Y, size).square() / T(3);
return true;
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
REGISTER_CPU_OPERATOR(
Cbrt,
UnaryElementwiseOp<
TensorTypes<float>,
CPUContext,
CbrtFunctor<CPUContext>>);
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
REGISTER_CPU_OPERATOR(
CbrtGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
CbrtGradientFunctor<CPUContext>>);
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
OPERATOR_SCHEMA(Cbrt)
.NumInputs(1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.IdenticalTypeAndShape()
.Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.")
.Output(
0,
"Y",
"*(type: Tensor`<float>`)* Output tensor calculated as the cbrt of the input tensor, element-wise.");
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
OPERATOR_SCHEMA(CbrtGradient)
.NumInputs(2)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.IdenticalTypeAndShapeOfInput(0);
namespace {
class GetCbrtGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"CbrtGradient",
"",
std::vector<std::string>{GO(0), O(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
REGISTER_GRADIENT(Cbrt, GetCbrtGradient);
} // namespace caffe2